XPS: FULL: Breaking the Scalability Wall of Shared Memory through Fast On-Chip Wireless Communication

XPS：FULL：通过快速片上无线通信打破共享内存的可扩展性壁垒

• 批准号: 1629431
• 负责人: Josep Torrellas
• 金额: $ 87.92万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1629431&HistoricalAwards=false
• 关键词: XPS; FULL; Breaking; Scalability; Wall

As transistor sizes continue to scale, we are about to witness stunning levels of chip integration, with 1,000 cores on a single die. At these processor counts, it has been an accepted tenet among many researchers that shared memory does not scale. The reason is the high hardware overhead of supporting fine-grain synchronization and communication between so many cores. This research seeks to disprove this. It shows that fine-grain data sharing is scalable with the use of fast on-chip wireless communication. The Principal Investigators (PIs) augment each core with a transceiver that enables on-chip broadcast in 5-7 nanoseconds, and design a multicore architecture that supports it. Then, the PIs implement synchronization and communication primitives and libraries that support fine-grain data sharing with an unprecendented low overhead. With these primitives, the PIs redesign popular runtimes such as OpenMP or Cilk, and rethink algorithms and applications. This effort contributes to multidisciplinary research and education on scalable parallel computing at the University of Illinois. The PIs will enhance the courses that they teach in parallel computer architecture, parallel compilation techniques, and parallel programming. They are also working with the department to broaden the course offerings with multidisciplinary undergraduate courses in the general area of parallel computing --- as part of Illinois' CS+X major structure, where X can be a large number of other disciplines. The work will also have an impact on industry, since it addresses a real, very timely technical problem: extraordinary on-chip integration coupled with unscalable fine-grain data sharing. The ability to work closely with IBM Research and Microsoft Research will be crucial.This is a cross-disciplinary effort that cuts across three areas: architecture, programming systems, and algorithms and applications. The architecture work focuses on supporting on-chip wireless communication by extending cache coherence transactions, trading-off wireless power for error rate, and supporting multiple wireless channels. The programming systems work focuses on redesigning the MPI communication primitives, making shared memory scalable for OpenMP and Cilk, and designing a best-effort API for application resiliency. The algorithms and applications work focuses on studying and developing algorithms and applications  that can take advantage of the architecture. The PIs study problems in the areas of graphs, numerics, dynamic programming, recognition-mining-synthesis, and MapReduce.

随着晶体管尺寸的不断扩大，我们即将见证令人惊叹的芯片集成水平，单个芯片上有1，000个核心。在这些处理器数量上，许多研究人员都认为共享内存不能扩展。原因是支持细粒度同步和这么多核之间的通信的硬件开销很高。这项研究试图反驳这一点。 它表明，细粒度的数据共享是可扩展的快速片上无线通信的使用。主要研究者（PI）为每个核心增加了一个收发器，使片上广播在5-7纳秒内完成，并设计了一个支持它的多核架构。然后，PI实现了同步和通信原语以及支持细粒度数据共享的库，其开销前所未有的低。有了这些原语，PI重新设计了流行的运行时，如OpenMP或Cilk，并重新思考算法和应用程序。这一努力有助于伊利诺伊大学可扩展并行计算的多学科研究和教育。PI将加强他们在并行计算机体系结构，并行编译技术和并行编程方面教授的课程。他们还与该部门合作，以扩大并行计算一般领域的多学科本科课程的课程设置-作为伊利诺伊州CS+X主要结构的一部分，其中X可以是大量的其他学科。这项工作也将对工业产生影响，因为它解决了一个真实的，非常及时的技术问题：非凡的片上集成加上不可扩展的细粒度数据共享。与IBM研究院和微软研究院密切合作的能力将是至关重要的。这是一项跨学科的工作，涉及三个领域：架构、编程系统以及算法和应用程序。该架构的工作重点是通过扩展高速缓存一致性事务来支持片上无线通信，权衡无线功率与错误率，并支持多个无线信道。编程系统的工作重点是重新设计MPI通信原语，使共享内存可扩展的OpenMP和Cilk，并设计一个最好的努力API的应用程序弹性。算法和应用程序的工作重点是研究和开发可以利用该架构的算法和应用程序。PI研究图形，数值，动态编程，算法挖掘合成和MapReduce领域的问题。

项目成果

Verifying safety and accuracy of approximate parallel programs via canonical sequentialization

通过规范序列化验证近似并行程序的安全性和准确性

• DOI: 10.1145/3360545
• 发表时间: 2019
• 期刊: Proceedings of the ACM on Programming Languages
• 作者: Fernando, Vimuth;Joshi, Keyur;Misailovic, Sasa
• 通讯作者: Misailovic, Sasa

V-Combiner: speeding-up iterative graph processing on a shared-memory platform with vertex merging

• DOI: 10.1145/3392717.3392739
• 发表时间: 2020-06
• 期刊: Proceedings of the 34th ACM International Conference on Supercomputing
• 作者: Azin Heidarshenas;Serif Yesil;Dimitrios Skarlatos;Sasa Misailovic;Adam Morrison;J. Torrellas

Aloe: verifying reliability of approximate programs in the presence of recovery mechanisms

• DOI: 10.1145/3368826.3377924
• 发表时间: 2020-02
• 期刊: Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization
• 作者: Keyur Joshi;V. Fernando;Sasa Misailovic

Replica: A Wireless Manycore for Communication-Intensive and Approximate Data

副本：用于通信密集型和近似数据的无线众核

• DOI: 10.1145/3297858.3304033
• 发表时间: 2019
• 期刊: ASPLOS '19: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
• 作者: Fernando, Vimuth;Franques, Antonio;Abadal, Sergi;Misailovic, Sasa;Torrellas, Josep
• 通讯作者: Torrellas, Josep